transformative Opportunities from pata Science and Big Data Analytics: applied to Photovoltaics

摘要

Understanding the overall lifetime performance of photovoltaic (PV) modules is essential to continue the cost reduction of solar energy, thereby increasing its contribution to the world's electricity needs and sustainability goals.1-2 In order to reach the 2030 SunShot goal of $0.03/kWh,3'4 the power degradation rates (representing the annual reduction in power output by a PV module) must be lowered to the 0.2%/year goal, so as to increase the lifetime of PV modules installed in diverse climates zones. Predicting the PV module performance over their 20- to 30-year product warranty or lifetime is typically done using traditional reliability approaches such as pass/ fail testing and materials qualification, yet this has proven insufficient. Current PV qualification tests have led to failures in real-world PV applications.5 Historical data from installed PV systems is the ideal source for understanding the magnitude and causes of module power loss and degradation, and for identifying how to extend the lifetime of PV modules to 50 years.